TY - GEN
T1 - Fast and accurate text detection in natural scene images with user-intention
AU - Wang, Liuan
AU - Fan, Wei
AU - He, Yuan
AU - Sun, Jun
AU - Katsuyama, Yutaka
AU - Hotta, Yoshinobu
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/12/4
Y1 - 2014/12/4
N2 - Text detection in natural scene images plays an important role in content-based image retrieval, especially user-guided text detection for human-computer interaction. In this paper, we propose a fast and accurate text detection method with user-intention in terms of tap gesture. Firstly, a user-intention slice descriptor is designed based on the estimated text property, which contains all the user interested texts, and fast heuristic features and accurate texture feature of decomposed connected components (CCs) are fed into cascade of Gentle Adaboost classifiers to eliminate non-text candidates, finally candidate texts, sharing the same property consistent with the seed CCs, are accumulated to a user-intention text line according to local and global permutation constraint. Experimental results demonstrate the effectiveness and robustness of the proposed method in comparison with the state-of-art methods.
AB - Text detection in natural scene images plays an important role in content-based image retrieval, especially user-guided text detection for human-computer interaction. In this paper, we propose a fast and accurate text detection method with user-intention in terms of tap gesture. Firstly, a user-intention slice descriptor is designed based on the estimated text property, which contains all the user interested texts, and fast heuristic features and accurate texture feature of decomposed connected components (CCs) are fed into cascade of Gentle Adaboost classifiers to eliminate non-text candidates, finally candidate texts, sharing the same property consistent with the seed CCs, are accumulated to a user-intention text line according to local and global permutation constraint. Experimental results demonstrate the effectiveness and robustness of the proposed method in comparison with the state-of-art methods.
KW - Candiate CCs elimination
KW - Gentle adaboost
KW - Scene text detection
KW - Text line accumulation
KW - Use-intention slice descriptor
UR - http://www.scopus.com/inward/record.url?scp=84919882925&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84919882925&partnerID=8YFLogxK
U2 - 10.1109/ICPR.2014.503
DO - 10.1109/ICPR.2014.503
M3 - Conference contribution
AN - SCOPUS:84919882925
T3 - Proceedings - International Conference on Pattern Recognition
SP - 2920
EP - 2925
BT - Proceedings - International Conference on Pattern Recognition
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference on Pattern Recognition, ICPR 2014
Y2 - 24 August 2014 through 28 August 2014
ER -